The use of microRNA expression profiling in the detection and prediction of Bovine Tuberculosis
The use of microRNA expression profiling in the detection and prediction of Bovine Tuberculosis
批准号:
10096799
负责人:
金额:
$24.55万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2024
资助国家:
英国
项目状态:
未结题
起止时间:
2024 至 --
中文摘要
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英文摘要
MI:RNA Ltd is a veterinary diagnostics company with a unique, patent-pending, biomarker testing technology and we aim to use our expertise to explore the early and accurate diagnosis of Bovine Tuberculosis (bTB).This project builds upon our previous successful Innovate UK funded trial which demonstrated the potential of our technology to detect early-stage Johne's disease, part of the same mycobacterial family as bTB. Bovine Tuberculosis is a chronic wasting disease with enormous implications economically, environmentally and in terms of productivity and sustainability for the UK farming sector. Despite decades of an extensive, policy driven eradication schemes, this notifiable disease remains prevalent in many parts of England. Current testing methods have limitations with poor sensitivity and frequent inconclusive reactors (IRs), hampering disease control efforts. The potential introduction of bTB vaccination (e.g. BCG vaccination) to the UK is a further complication, as animals can test falsely positive after vaccination. Consequently, improved diagnostics will result in enhanced disease control leading to increased productivity, mitigation of economic losses and assistance in achieving a sustainable and safe, carbon neutral business model.This project will combine MI:RNA's innovation with the research expertise of colleagues within Scotland's Rural College (SRUC). The assembled team will work with the APHA, the UK government animal health laboratory, from whom samples and data will be sourced, along with their specialist and experience guidance.Project phases:Phase 1: A bespoke panel of microRNA (miRNA) biomarkers will be created specific to bTB pathology. This will be trialled with negative control and bTB positive serum samples to generate expression profiles of these markers, which will be analysed by advanced supervised AI algorithms, generating an initial modelling system for detection of bTB.Phase 2: This phase will see the model being optimised and challenged with longitudinal time course samples from previous APHA studies of bTB challenged animals. This will allow further refinement of the model for improving early-stage diagnostic accuracy.Phase 3: This phase will see the mature model being challenged with the task of differentiating between bTB vaccinated animals and true bTB cases, success here would be hugely beneficial to planned bTB vaccination programmes.The outcomes of these trials will be released publicly in peer-reviewed academic journals and protected with patents, and we will finalise our next stage research and development objectives. This will feed directly into our commercialisation plan to make the product available to the market, positively impacting the UK livestock sector.
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